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Banks define and pursue innovation by questioning its core drivers: internal factors like culture, leadership, and strategy, versus external collaborations with fintechs, startups, and tech providers. This debate underscores the tension between maintaining control and embracing partnership-driven transformation. In this discussion with IBM’s Paolo Sironi, Charbel Safadi–Zafin CEO–discusses AI-driven innovation in banking, urging institutions to shift from tech aspirations to orchestrating high-value financial services via external ecosystems. Banks should prioritize customer journeys, product design, and loyalty over foundational AI development, dominated by tech giants. Strategic investments beyond digitization—reimagining bundling and value creation—are key. Ultimately, culture and execution speed differentiate winners.
This is a timely and pertinent question, particularly in light of recent discussions I have held with senior leaders at some of the largest global banks regarding AI and innovation. Over the past 10 to 15 years, many banks have positioned themselves as technology companies operating under a banking license. However, in the AI era, this paradigm no longer applies. Banks must realign their focus toward their core identity as financial institutions dedicated to delivering differentiated, high-impact financial services achieved through intelligent orchestration rather than foundational innovation.
Banks excel at identifying and adopting technological capabilities that drive business transformation, including enhancing customer experiences, optimizing internal processes, and increasingly, empowering employees. Most banks are not equipped to lead AI innovation at a foundational level. With the exception of a few global institutions, they are not engaged in developing foundational models or advancing the frontiers of AI research; such endeavors are the domain of technology giants that invest billions in AI development. The more relevant inquiry is whether AI innovation arises internally within banks or extends across an ecosystem of technology partners.
In the AI-driven landscape, banking innovation will prioritize a deep understanding of core business operations, anticipation of market trends and competitive dynamics, and the use of AI, often delivered as a service, to orchestrate transformative experiences spanning customer and employee interactions, product design, delivery, marketing, and servicing. This shift requires cultivating an organizational culture that readily adopts and integrates orchestration tools, such as API-driven platforms or agentic AI capabilities, while accommodating frequent model updates and continuous improvement.
Selected Tier 1 institutions, with multibillion-dollar technology budgets, are industry exceptions rather than the standard, and should not serve as a universal benchmark. For Tier 2 and regional banks, success hinges on establishing leadership within their specific domains through ongoing collaboration with ecosystem providers who offer continuous advancements.
“Banks need to move past the idea that they are tech-first companies. Instead, they should refocus on being exceptional financial service providers, enabled by technology but not defined by it. The future of innovation in banking lies in mastering the orchestration of external capabilities to create distinctive, high-value experiences that customers want.”
Tapping into the power of the ecosystem, especially now in the SaaS world, enables them to do so faster than the competition.
This innovation shift is a significant leap for most financial institutions. Not because they lack the capability, but because their legacy structures make it incredibly hard to move. The traditional banking model is vertically aligned, with product, servicing, and operations all sitting in silos. That vertical construct was built for a different era, and it limits the kind of cross-functional orchestration required for true innovation today. To enable composable, business-led innovation, banks must fundamentally rethink how they budget, how they organize around products and services, and how they design for flexibility rather than control.
In today’s world, copying a product or a strategy can happen almost instantly. Speed is no longer the barrier. The real barrier is culture. The organizations that will succeed are those that build a culture centered around identity, purpose, and adaptability—knowing what they’re great at, where they need help, and creating the structure to partner and execute with agility. That means redefining what the organization looks like and identifying the “minimal viable foundation” needed to operate in this new paradigm.
Ten years ago, the innovation bar was launching a slick mobile app with Face ID. Today, banks are back to competing on the fundamentals: delivering real value, helping customers build wealth, earning long-term loyalty, not just simplifying digital access. Yet, the reality is we now have tens of thousands of banks globally, all with massive tech budgets, all building the same widgets. That’s not innovation. That’s duplication. And it’s time to break the cycle.
Banks must stop looking inward and assuming they can build everything themselves. That approach has consistently destroyed shareholder value across the industry. Instead, they must embrace the broader ecosystem, technology and business partners alike, to accelerate outcomes. Importantly, regulatory constraints, both real and perceived, also play a role. The highly regulated environment in which banks operate can slow the pace of change, create uncertainty around compliance, and sometimes reinforce risk-averse cultures. Leading organizations are those that work collaboratively with regulators and ecosystem partners to find compliant paths to innovation, rather than letting regulation be a default excuse for inertia.
At the heart of resistance to innovation in banking is the challenge of translating ambition into action at the enterprise level. Consider the rise of neobanks and the disruptive force of stablecoins, which are fundamentally redefining concepts such as deposits, interchange fees, and overall value creation. While traditional banks may grasp their current models, the critical challenge lies in cultivating a mindset attuned to impending transformations. This demands a paradigm shift from vertical, siloed approaches, which are centered on individual profit-and-loss statements and isolated products, to horizontal, integrated business models that span the entirety of a customer’s financial journey, delivering seamless, end-to-end value.
Such a transition, however, is impeded by entrenched structures: incentive models and organizational frameworks that perpetuate silos. For example, customer loyalty often remains fragmented. Banks may reward a premium credit card customer more than a client with a $2 million mortgage, simply because incentives and decision-making remain stuck at the product level, not at the enterprise or relationship level.
This is precisely where fintech disruptors have excelled, dismantling silos to offer orchestrated, bundled solutions that address customers’ needs comprehensively.
The inability to access real-time data across the enterprise further compounds the challenge. Many banks still rely on fragmented, batch-based data and manual processes, making it hard to sense and respond to customer or market needs quickly. By contrast, fintechs and digital-native firms are built on integrated data platforms and can deliver bundled, orchestrated solutions that address the full customer journey.
Ultimately, what prevents bankers from embracing the shift is not just culture or incentives, but the inability to rewire business models, processes, and data flows at the enterprise level. Overcoming this requires bold leadership, investment in enterprise architecture, and a willingness to measure success by holistic outcomes, not just product performance.
This is an excellent question, and my viewpoint is straightforward: at its core, what defines a bank? It is not merely an assemblage of financial products, but rather the manner in which those products are thoughtfully packaged, seamlessly delivered, and ultimately leveraged to generate genuine value for customers.
Over the past decade of fintech evolution, banks have invested substantially in digitizing access and enhancing simplicity. To their credit, they have executed this admirably. Features such as five-minute onboarding, instantaneous account setup, and effortless switching have become standard. However, this very success has led to commoditization. With every institution offering similar digital experiences, customers now face minimal barriers to migration. While these extensive technological commitments have effectively minimized friction and optimized cost structures, they have fallen short in fostering substantive product innovation or holistic value creation throughout the customer lifecycle. This challenge extends beyond retail banking to encompass corporate and commercial segments as well.
Envision, then, a strategic pivot: redirecting that same ingenuity and capital toward reimagining product design, sophisticated packaging, robust loyalty programs, and tiered offerings. This approach strikes at the essence of banking, which is crafting and servicing financial solutions that deliver tangible, enduring value.
Critically, investing in transparency and supporting customers’ long-term financial well-being should become central pillars of this transformation. When complemented by strategic alliances within the technology and AI ecosystem, such efforts can catalyze profound transformations, benefiting customers and employees alike.
My counsel to bankers is clear: return to the fundamentals of banking and reinvigorate the spirit of innovation and creativity that once defined the industry, when collective ambition drove pioneering product advancements. The moment has arrived to prioritize true innovation in banking, transcending mere digitization to embrace its transformative potential.
Banks have indeed established a solid foundation by expanding their horizons beyond internal operations, increasingly embracing external ecosystems through cloud computing and Software-as-a-Service (SaaS) solutions. Many financial institutions now actively consume these services, cultivating the essential competencies to integrate and leverage external capabilities effectively. However, this proficiency remains underdeveloped in key respects.
Consider customer relationship management (CRM) systems as a prime illustration: banks allocate billions to adopt standardized CRM tools, presuming that such implementations will resolve entrenched challenge in their sales processes. Yet, they often overlook the imperative to fundamentally reimagine how products are marketed, sold, and consumed. Instead, institutions frequently commit to a single tool for extended periods, spanning five, ten, or even twenty years, and erroneously equate this longevity with genuine innovation.
In the contemporary landscape, particularly with the advent of AI and agentic technologies, true innovation demands agility, adaptability, and perpetual evolution. Technological tools advance at an extraordinary pace; what represents the vanguard today may become obsolete within a mere year. While leading technology companies have surged ahead, transcending conventional development paradigms through these breakthroughs, many banks lag significantly behind, still deliberating over the adoption of rudimentary AI applications or contemplating the construction of proprietary models. Meanwhile, tech titans invest billions in foundational advancements. That’s not being AI-first; it’s missing the point.
To fully capitalize on the transformative potential of generative and agentic AI, business professionals require a foundational grasp of technological principles, a development that is already underway. On the consumer front, individuals are engaging with generative AI tools in their daily routines, often unwittingly acquiring proficiency, much as society did during the internet’s emergence in the 1990s. In that era, enterprises relied on intricate layers of technology merely to analyze data, generate insights, and implement actions.
Today, generative and agentic AI abstract away much of that complexity, removing the need for vast internal engineering resources or costly computational infrastructure to drive innovation. AI is now seamlessly embedded into the core of business operations, empowering business and product owners to act independently with the tools and capabilities they need, always readily available, without dependence on IT departments.
“Ultimately, AI is our “superpower to become superhuman,” fully embedded through universal training and cultural integration. Those resistant to adaptation will struggle to thrive.”
Artificial intelligence is not an experimental pursuit for us; it underpins our core operations. Less than two years ago, we built a top-tier team and integrated AI faster than peers in our regulated sector, prioritizing compliance, explainability, and traceability. In engineering, adoption is total: all developers use generative AI tools, with products AI-assisted from development to deployment. We’ve maintained R&D spending yet increased productivity by 40%, delivering direct profitability gains unmatched by any other technology used to date.
Beyond engineering, generative AI infuses the organization. 95% of staff use generative AI daily across finance, HR, marketing, and cybersecurity. Finance’s month-end close dropped from 14 to two days, aiming for one; marketing has consolidated its technology stack and reallocated resources, enabling us to significantly boost both output and brand impact. Ultimately, AI is our “superpower to become superhuman,” fully embedded through universal training and cultural integration. Those resistant to adaptation will struggle to thrive.
The more effectively we perform, the greater the value we provide to our clients. I frequently emphasize to CIOs and CEOs that we have transitioned from a traditional product-centric company to becoming the “company of yes”–within the domains where we operate. This signifies our ability to respond affirmatively and with speed and assurance to customer requirements where we have platform flexibility and capability. In the past, product companies adhered to protracted development cycles: hypothesizing, designing, building, testing, selling, and implementing, which often spanned months or years. AI has revolutionized this for us. Today, we are able to accelerate development and deployment cycles significantly. What once took months or years can now be accomplished in weeks, with ideation, coding, and deployment supported by AI-enhanced site reliability engineers (SREs). This fosters a perpetual cycle of innovation, enabling us to transform client needs into tangible solutions more swiftly than ever before.
“In the past, product companies adhered to protracted development cycles: hypothesizing, designing, building, testing, selling, and implementing, which often spanned months or years. AI has revolutionized this for us. Today, we are able to accelerate development and deployment cycles significantly”
In the realm of SaaS product development, the longstanding assumption that a sufficiently compelling offering will endure indefinitely no longer applies. Today, every employee emerges as a potent generator of intellectual property through artificial intelligence, while each customer interaction and sales engagement presents an avenue to cultivate and refine value. When industry observers suggest that “SaaS is dead,” what they truly underscore is the imperative for a perpetual cycle of product innovation.
The paradigm has evolved beyond mere “software-as-a-service” to encompass dynamic, agentic, and orchestrated experiences, where intelligent agents fluidly traverse platforms, ecosystems, and organizational boundaries. At Zafin, we witness this transformation directly: the antiquated SaaS model, where companies construct a solution once, deploy it, and anticipate unchanged usage for decades, is obsolete. In its stead, adaptability and relentless evolution define the new benchmark for success.
Today, empowered, tech-enabled business teams expect to shape solutions as they go, tailoring products, workflows, and experiences in real time, often without heavy IT involvement.
The rise of low-code/no-code tools, modular SaaS architectures, and AI powered platforms now allows teams to rapidly adjust and personalize offerings for different customers, business lines, or use cases. As a result, customization has become continuous, iterative, and much more embedded in the way modern organizations operate.
At our organization, for example, we are pioneering “agent teams:” groups of AI that ingest user stories or business challenges and dynamically assemble virtual teams spanning design, architecture, compliance, and security to iterate and construct solutions without interruption. This is far from conceptual; it lets business leaders focus on outcomes, rather than technical details, and accelerates the ability to adapt to new opportunities or requirements.
In a recent engagement with a bank’s C-suite, comprised of business executives rather than technologists, we intentionally focused the conversation away from technical details. Instead, we probed the core: “What is the business challenge? What is the desired outcome?” With clarity established, AI emerges as the catalyst, enabling the orchestration of thousands or even millions of agents in pursuit of enterprise-wide objectives.
The winners in this environment will not be those with the most sophisticated underlying AI, but those who can rapidly deploy and integrate new capabilities and foster a culture where teams are encouraged to adapt, experiment, and personalize without friction.
Ultimately, the next era of customization is about speed, integration, and alignment with business goals, making it possible for teams to continuously refine and evolve what they deliver, in partnership with technology.
It is here that the platform assumes pivotal importance, furnishing the essential insights and tools for effective governance. Incremental enhancements are not enough if systems remain disconnected; without robust integration, holistic enterprise management becomes unattainable.
Banks must diminish the dominance of their legacy core systems by fostering a fundamental shift in perspective. When business leaders demand greater agility, such as accelerated product launches, dynamic pricing, or innovative bundling, CIOs frequently cite the constraints of the outdated core and respond with, “We can’t.” This entrenched resistance is the crux of the issue.
Rather than wholesale replacement, the core requires recalibration: preserve its stability for essential functions while relocating critical capabilities, such as product management, pricing strategies, and personalization to the periphery through strategic partnerships and platforms. This empowers business teams to achieve market victories in the present, rather than deferring them for years.
Prioritizing core modernization before pursuing business transformation risks squandering valuable time and eroding market position. While outright failure may be averted, the consequences include diminished return on investment, compressed margins, and waning shareholder value.
Instead, banks should prioritize collaboration with business stakeholders: discern their precise needs, affirm possibilities more readily, and cultivate an ecosystem of supportive technologies. By strategically contracting the core’s influence, both technically and operationally, banks can advance with speed, ensuring sustained competitiveness
I initiated this dialogue by highlighting the pivotal role of a bank’s culture as its true differentiator, and it is here that the conversation comes full circle.
In the present landscape, access to state-of-the-art computational resources and artificial intelligence is no longer constrained by organizational scale. Whether comprising a nimble team office or a vast enterprise of 50,000 engineers, all entities now enjoy parity in capabilities. The decisive factor distinguishing victors from the rest lies in organizational culture and the speed with which it enables execution.
This insight constitutes the paramount lesson I have gleaned, particularly from my 21 years at a prominent technology firm, a tenure rich in invaluable experiences, illuminating both exemplary practices and pitfalls to avoid. The stark reality in large institutions is that entrenched silos and vertical structures invariably impede progress and thwart transformative initiatives. Again and again, a robust culture paired with swift execution triumphs over mere scale.
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